1. The Field of the Invention
The present invention relates to a method of evaluating the surface characteristics of opaque materials. More particularly, the present invention is directed to a method of evaluating qualitative and quantitative surface characteristics of a opaque film by measuring the intensity of reflectance therefrom across a spectrum of electromagnetic wavelengths, where measurements are taken with a reflectance detector at a plurality of reflectance angles.
2. The Relevant Technology
It has become desirable to measure or otherwise analyze surface characteristics such as the microscopic surface roughness of certain opaque materials during the fabrication of the opaque materials. An example of one material for which it is highly beneficial to measure surface characteristics is polycrystalline silicon (polysilicon). Polysilicon is used in the semiconductor manufacturing industry as a conductive layer and has significant advantages over other conductive materials in that it can withstand the high temperatures that are often required in subsequent manufacturing steps, and because it has the same electron affinity as single crystal silicon. Polysilicon is a solid material which is comprised of pure silicon crystallites or xe2x80x9cgrainsxe2x80x9d separated by grain boundaries. Consequently, the morphology of polysilicon is generally characterizable by the size of the individual crystals and the width of the grain boundaries that separate the crystals.
Polysilicon is typically formed as a film on silicon wafers in the process of manufacturing integrated circuits. Careful control of reactant gas flow, temperature, and pressure is required for consistent polysilicon film production. Within even these narrow parameters, however, the surface qualities of the polysilicon film can vary dramatically.
A recent development in polysilicon applications involves growing intentionally rough films for use as capacitor plates in integrated circuits. The roughness of the surface of these films serves as a means to increase the effective surface area of the capacitor plate while occupying a minimum of wafer space. When the polysilicon is grown with large grains, in the order of 60 nm or more, it is considered hemispherical grain polycrystalline silicon (HSG polysilicon). HSG polysilicon is preferred for other semiconductor manufacturing processes as well, and in each case must be deposited under the proper conditions to maximize its surface area.
HSG polysilicon is typically formed in one of two manners. In the first manner of polysilicon formation, the HSG polysilicon is formed by chemical vapor deposition with an appropriate chemistry, typically comprising silane in an appropriate chamber under certain predetermined process conditions. The second technique comprises depositing a planar smooth film of highly amorphous polysilicon which is appropriately doped with a seeding dopant such as phosphine, arsine or disilane. These dopants are then used as nucleation sites for forming grains within the crystalline structure of the polysilicon. The grains are formed during an anneal step during which the film surface rearranges itself into grains, providing a rough surface area.
Integrated circuits are currently grown in large batches, and inadvertent change of even one parameter of the HSG production process could reduce the surface area of the film to such a degree as to cause a failure condition. As an example, when an HSG polysilicon film being used to form capacitor plates is deposited under less than optimal conditions, the surface area of the capacitor plate may be insufficient, resulting in capacitors that fail to hold a charge sufficiently. When the capacitors are used to form a DRAM memory cell, for instance, the DRAM memory cell will as a result fail to meet refresh rates. A defect condition results which can reduce fabrication processing yield significantly.
Consequently, the precise control of polysilicon deposition is desirable to the preferable practice of semiconductor manufacturing processes. In order to maintain the necessary control over the manufacturing process, a method of evaluating the surface roughness of the HSG polysilicon is needed, both for process development and in-process monitoring. Furthermore, the method needs to be flexible, in order to meet the very different demands of both process development and in-process monitoring.
Process development requires a method that is accurate and dependable, and capable of providing detailed information as to specific surface characteristics, including at least surface roughness, grain size, and surface area. An in-process monitoring method need not necessarily provide highly detailed information, but should at least be able to determine when a variation in surface characteristics takes place. It should also be suitable to be conducted in-situ, and should not lower throughput.
Aluminum is a further example of a material for which a method of evaluating the surface characteristics is needed. In practice it has proven difficult to maintain the deposition parameters for aluminum at appropriate levels in order to result in a smooth surface of the deposited aluminum In order to verify the smoothness of deposited aluminum and determine exactly how the parameters must be adjusted to maintain a smooth surface, a method for the in-process determination of the surface roughness of the aluminum is desirable.
The prior art has employed a number of methods for evaluating the surface characteristics of opaque materials. None of the prior art methods, however, has proven fully satisfactory for both product development and in-process evaluation of the surface characteristics of materials such as HSG polysilicon and aluminum.
One method previously used for analyzing surface characteristics of substrate materials is scanning electron microscopy (SEM). Using the SEM method, the sample is bombarded with electrons, and the electrons are then measured for surface characterization information as they return to the device. One limitation of this method is that the electrons do not penetrate deeply into the sample. Thus, SEM has proven helpful for analyzing lateral dimensions of surface roughness, but is very limited in analyzing vertical dimensions. Furthermore, SEM is generally destructive of the sample, has slow feedback times, and cannot be used in-process, during fabrication. It is also difficult to determine qualitative data about the sample using SEM. Furthermore, SEM cannot be used to determine precise grain size and surface area of highly granular samples. SEM analysis would be highly dependent upon the operator""s judgment for such a characterization.
Another method previously used is atomic force microscopy (AFM). AFM utilizes a very small stylus, similar to a record needle. The stylus is scanned across the sample, back and forth over a small area, while a laser is reflected off of a platform located on the stylus. The deflection of the stylus is then measured by the variations in the returned laser light. The laser detector detects the reflected laser light, which is a direct result of the vertical movement of the stylus. This method provides very high resolution, even down to atomic resolution for certain samples, but has proven incapable of producing repeatable results. Furthermore, AFM is a very technical and demanding process, requiring highly-trained operators. AFM is also highly susceptible to environmental noise and surrounding vibrations. Additionally, the AFM contact method is somewhat destructive. While it does not destroy a whole wafer, it does destroy at least the part that is being tested. Thus, AFM has proven impractical for implementation on an in-process basis.
A further method previously used in the art is tunneling electron microscopy (TEM). Using TEM, a sample is prepared on a very thin slice of silicon, then electrons are bombarded through the sample. The density of the electrons are measured on the other side of the sample with a detector. The pattern the electrons make on the detector as a result of the material that is being passed through is used to determine the size of the grains and their locations. This is also a very sensitive technique which can measure down to a very small feature size and can give calibrated results. Once again, however, the process is very time consuming, and involves a very high skill level of the operator. TEM is also a destructive method that cannot be conducted in-process.
A further method of surface evaluation is described in a paper entitled xe2x80x9cRapid Characterization of Polysilicon Films by Means of a UV Reflectometerxe2x80x9d by G. Harbeke, E. Meir, J. R. Sandercock, M. Tjetjel, M. T. Duffy, and R. A. Soitis, RCA Review, Vol. 44, March 1983. Therein, a method of characterization of polysilicon films by means of a UV reflectometer is taught. The UV reflectometer is used to measure the reflectance of polysilicon on semiconductor wafers at one of two fixed wavelengths in the ultraviolet spectral region. Particularly, it measures the wavelengths at either 280 nm or at 400 nm, depending upon the application. The wavelength of 280 nanometers is used for in-process quality control of dust and defect detection. The wavelength of 400 nanometers, which has been found to probe to greater depths, is disclosed as being used to probe for bulk structural perfection in polycrystalline films.
The reflectometer uses a deuterium lamp, which provides a continuum light source. A chopper is used to alternately reflect light to a sensor from the sample and from blades on the chopper. The detector uses a silicon photovoltaic device with an enhanced UV response to detect the fraction of light reflected. The electrical signals from the detector are used to form a second signal which is normalized to the difference of the reflectance from the chopper minus the reflectance from the sample. The result is then plotted by reflectance and corresponds generally to surface smoothness and defect conditions.
This method has proven satisfactory for measuring surface defects and bulk characteristics of highly polished polysilicon films. Once again, however, sufficient information is not provided to characterize HSG polysilicon films. Such data from one of the wavelengths at 280 nm and 400 nm becomes somewhat inconsistent when the silicon passes a certain roughness, and provides only a moderate degree of information about the surface area of rougher films. Furthermore, no method of quantifying the raw reflectance data into useful information about surface characteristics is provided.
In order to better understand why the above method is inadequate for characterizing HSG polysilicon films, the graphical depictions of FIGS. 1 through 4 are provided. Therein are shown four different samples of HSG polysilicon. The sample of FIG. 1 has a relatively small grain size, uniform grains, and large boundary spaces between the grains. The sample of FIG. 2 is of a larger grain size and still of relative uniformity. In FIG. 3, an even larger grain size is depicted, with relatively uniform grains. FIG. 4 depicts a yet larger grain size, with somewhat irregularly shaped grains. The HSG polysilicon films graphically depicted in FIGS. 1 through 4 may be used, by way of example, as capacitor plates in integrated circuits.
The single wavelength method described above will detect a difference in reflectance between each of these samples, but has been found incapable of transforming that difference into a quantification of surface characteristics or of predicting surface area with a high degree of precision. This is due in part to the lack of information provided by each single wavelength about surface characteristics such as grain size, grain shape, grain density, and grain boundary size, all of which affect the total surface area and will effect the measured reflectance differently.
Thus, from the above discussion it can be seen that the need exists in the art for a method of evaluating the surface characteristics of opaque materials such as polysilicon films during process development. Furthermore, there is a need for a method of evaluating the surface characteristics of such materials which can be conducted in-process without destroying the sample, which can be conducted rapidly, and which can be conducted by operators that are not extensively trained. Such a method is particularly needed which is highly accurate in quantitatively determining particular surface characteristics such as surface area under varying parameters, and which can be used for opaque films of a high surface roughness.
The present invention seeks to resolve the above and other problems that have been experienced in the art. More particularly, the present invention constitutes an advancement in the art by providing a method for evaluating the surface characteristics of opaque materials with a reflection intensity detector and thereby quantitatively characterize the surface conditions of the opaque materials. By measuring the intensity of a reflected electromagnetic radiation (EMR), such as visible or invisible light, from a surface of an opaque material at different angles for a given angle of incident EMR, surface characteristics thereof can be derived, such as whether the surface is smooth, if it has prismatic irregularities, or if it has hemispherical irregularities.
The inventive method can be conducted ex situ for product development or in-process for production monitoring. A single wavelength or up to a full spectrum of ultraviolet wavelengths can be used. Additional information can also be learned about the surface characteristics of the opaque materials by changing the angle incidence and the angle of the reflection at which a intensity detector, such as a UV reflectometer, measures reflectance intensity.
The method of the present invention in one embodiment comprises the use of a UV reflectometer to measure the set of reflectances of a test sample of unknown surface characteristics covering a continuum of spectra and a plurality of UV reflectometer positions, and then to compare the reflectance data against reflectance data taken from a collection of control samples having known surface characteristics at the same plurality of UV reflectometer positions. The reflectances of the control samples are collected in a calibration matrix, which may be a graphical plot or may be part of a computer software program, in the form of a look-up table. The reflectances of the test sample are compared to the reflectances of the control samples across the spectrum. By the comparison, the desired surface characteristics are thereby predicted by finding the closest fit among the reflectance sets of the control samples in the calibration matrix, and by calibrating the corresponding known surface characteristics of the control sample with the closest fit to the test sample.
Thus, a first step in the method of the first embodiment of the present invention is to provide a calibration matrix of reflectance data of control samples of known surface conditions at a plurality of UV reflectometer positions. The control samples are preferably categorized together by material type, such that a material such as polysilicon would be categorized together, and other materials such as aluminum would be categorized separately. In creating a calibration matrix, the surface characteristics of the control samples are first independently evaluated using an independent method such as SEM, TEM, or AFM.
The reflectances of each control sample are taken across the spectrum of ultraviolet light wavelengths at a plurality of angles of reflection and are included in a calibration matrix for each specific material. Each set of reflectances of each control sample can be included as a separate file, or the set of reflectances of any one control sample may be further refined to a single data point or several data points representative of each control sample by an algorithm which gleans information from the broad spectrum and refines it down to the one or several data points. These data points are correlated with the respective surface characteristics such as surface area or grain size and incorporated into the calibration matrix.
A further step is to measure the reflectances of the test sample across the same spectrum of ultraviolet wavelengths and at the same plurality of angles of reflection, preferably one measurement for each integer wavelength in the range of between about 220 and about 450 nanometers. In so doing, the light is reflected from the angle of incidence from the test sample and collected again in a sensor. The intensity of the light returning to the sensor is then quantified as the reflectance at each angle of reflection that the UV reflectometer is positioned at. The lower wavelength range limit of around 220 nanometers is typically a limitation of the reflectometer, and the upper wavelength range limit of about 450 nanometers is typically taken at or about the boundary where the material being measured becomes translucent to the light.
The next step is to compare the reflectances of the test sample to those of the control samples collected in the calibration matrix. In so doing, a suitable mathematical algorithm may be used. One such algorithm is the partial least squares method. The partial least squares method compares the set of reflectances of the test sample with the set of reflectances of each of the control samples in the calibration matrix and determines the closest fit. The surface conditions to be determined, such as surface area, surface roughness, grain size, and grain boundary size, which are known for the closest fitting control sample in the calibration matrix, are assigned as the calibrated result. Any algorithm by which one series of data may be found to correspond to another series of data with a desirable level of accuracy in a calibration or look-up method may be used for the comparison.
Another possible algorithm, given by way of example, compares the maximum reflectance in a given range of wavelengths with the minimum reflectance in a second given range of wavelengths, subtracts the minimum reflectances from the maximum reflectance and stores the difference as a delta value for each of a plurality angles of reflection. The delta value is then plotted on one axis of a chart against the maximum reflectance on a second axis. Thus, the spectra of wavelengths is reduced to a single point for each angle of reflection. This point may then be easily compared to other such points which are plotted or stored in the calibration matrix. The calibration matrix can be stored in a computer data base or charted in a graphical plot. This embodiment is particularly useful for ex situ product development.
A second embodiment is better suited for in-process product monitoring and comprises selecting a wavelength or group of wavelengths within the ultraviolet spectrum wherein the sensitivity to the surface characteristics being monitored is greatest. The reflectance measurement is conducted at a single ultraviolet wavelength or across a spectrum of multiple ultraviolet wavelengths, depending on how much information is needed and how consistent the information must be. The reflectances are preferably measured during or directly after the formation of the film to be monitored. Preferably, the measurement is conducted during a cooling stage in the film manufacturing process. In the monitoring of HSG polysilicon, for example, reflectance measurement can be conducted directly on an HSG polysilicon forming machine.
The measured reflectances, which are preferable made for a plurality of angles of reflection, can be used to provide quantitative data regarding the surface characteristics of the film, or can be compared to a range of acceptable reflectances which has been predetermined by measuring the reflectances of a set of control samples with known surface characteristics.
The method of the present invention in the described embodiments can be used for evaluating the surface characteristics of a variety of materials, and is especially beneficial for use in determining the surface area of polysilicon during the production of capacitator plates in integrated circuits. The method can be conducted in-process, is nondestructive, and requires a minimum of technician training. Furthermore, it is minimally sensitive to atmospheric conditions and vibrations. Also, it works effectively for materials of low surface roughness as well as for materials with high surface roughness. Furthermore, the method is capable of accurately providing a quantitative evaluation of a desired surface characteristic.
These and other features and advantages of the present invention will become more fully apparent from the following description and appended claims, or may be learned by the practice of the invention as set forth hereinafter.